Abstract—Ontology matching or finding similarities between concepts of different ontologies, has many applications today. One automatic approach for finding these similarities is by leveraging machine learning techniques. In this paper we propose a new method in which a text corpus is used as the source of knowledge in conjunction with a machine learning method to find matchings between two ontologies.
Index Terms—Ontology matchin, machine learning, text corpus.
Besat Kassaie is with Islamic Azad University Science and Research Branch, Tehran, Iran (e-mail: Besat_k@yahoo.com)
Maseud Rahgozar is with ontrol and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University College of Engineering, University of Tehran, Tehran, Iran (e-mail: Rahgozar@ut.ac.ir）
Alireza Vazifedoost is with chool of Electrical and Computer Engineering, University College of Engineering, University of Tehran, Tehran, Iran (e-mail: Vazifehdst@ut.ac.ir)
Cite: Besat Kassaie, Alireza Vazifedoost, and Maseud Rahgozar, "Application of Textual Corpus in Ontology Matching," International Journal of Information and Education Technology vol. 2, no. 6, pp. 638-642, 2012.